Since TRIPOD does not contain sentiment annotations, we instead obtain
silver-standard labels via COSMIC [1]}, a
commonsense-guided framework with state-of-the-art performance for
sentiment and emotion classification in natural language
conversations. Specifically, we train COSMIC on MELD
[2]}, which contains dialogues from episodes of the TV
series Friends and is more suited to our domain than other
sentiment classification datasets
(e.g., [3]}, [4]}).
After training, we use COSMIC to produce sentence-level sentiment
predictions for the TRIPOD screenplays. The sentiment of a scene
corresponds to the majority sentiment of its sentences. We project
scene-based sentiment labels onto shots using the same one-to-many
mapping employed for TPs.
